Copyright | (c) 2018-2019 Andrew Lelechenko |
---|---|
License | MIT |
Maintainer | Andrew Lelechenko <andrew.lelechenko@gmail.com> |
Safe Haskell | Safe-Inferred |
Language | Haskell2010 |
Lazy infinite streams with O(1) indexing.
Synopsis
- memoize :: (Word -> a) -> Word -> a
- memoizeFix :: ((Word -> a) -> Word -> a) -> Word -> a
- data Chimera v a
- type VChimera = Chimera Vector
- type UChimera = Chimera Vector
- tabulate :: Vector v a => (Word -> a) -> Chimera v a
- tabulateFix :: Vector v a => ((Word -> a) -> Word -> a) -> Chimera v a
- tabulateFix' :: Vector v a => ((Word -> a) -> Word -> a) -> Chimera v a
- iterate :: Vector v a => (a -> a) -> a -> Chimera v a
- unfoldr :: Vector v b => (a -> (b, a)) -> a -> Chimera v b
- cycle :: Vector v a => v a -> Chimera v a
- fromListWithDef :: Vector v a => a -> [a] -> Chimera v a
- fromVectorWithDef :: Vector v a => a -> v a -> Chimera v a
- interleave :: Vector v a => Chimera v a -> Chimera v a -> Chimera v a
- index :: Vector v a => Chimera v a -> Word -> a
- toList :: Vector v a => Chimera v a -> [a]
- tabulateM :: (Monad m, Vector v a) => (Word -> m a) -> m (Chimera v a)
- tabulateFixM :: (Monad m, Vector v a) => ((Word -> m a) -> Word -> m a) -> m (Chimera v a)
- tabulateFixM' :: forall m v a. (Monad m, Vector v a) => ((Word -> m a) -> Word -> m a) -> m (Chimera v a)
- iterateM :: (Monad m, Vector v a) => (a -> m a) -> a -> m (Chimera v a)
- unfoldrM :: (Monad m, Vector v b) => (a -> m (b, a)) -> a -> m (Chimera v b)
- mapSubvectors :: (Vector u a, Vector v b) => (u a -> v b) -> Chimera u a -> Chimera v b
- traverseSubvectors :: (Vector u a, Vector v b, Applicative m) => (u a -> m (v b)) -> Chimera u a -> m (Chimera v b)
- zipSubvectors :: (Vector u a, Vector v b, Vector w c) => (u a -> v b -> w c) -> Chimera u a -> Chimera v b -> Chimera w c
- zipWithSubvectors :: (Vector u a, Vector v b, Vector w c) => (u a -> v b -> w c) -> Chimera u a -> Chimera v b -> Chimera w c
- zipWithMSubvectors :: (Vector u a, Vector v b, Vector w c, Applicative m) => (u a -> v b -> m (w c)) -> Chimera u a -> Chimera v b -> m (Chimera w c)
- sliceSubvectors :: Vector v a => Int -> Int -> Chimera v a -> [v a]
Memoization
memoizeFix :: ((Word -> a) -> Word -> a) -> Word -> a Source #
For a given f
memoize a recursive function fix
f
,
caching results in VChimera
.
This is just a shortcut for index
.
tabulateFix
.
When a
is Unbox
, it is faster to use
index
(tabulateFix
f
:: UChimera
a
).
memoizeFix f n = fix f n
For example, imagine that we want to memoize Fibonacci numbers:
>>>
fibo n = if n < 2 then toInteger n else fibo (n - 1) + fibo (n - 2)
Can we find fiboF
such that fibo
= fix
fiboF
?
Just replace all recursive calls to fibo
with f
:
>>>
fiboF f n = if n < 2 then toInteger n else f (n - 1) + f (n - 2)
Now we are ready to use memoizeFix
:
>>>
memoizeFix fiboF 10
55>>>
memoizeFix fiboF 100
354224848179261915075
This function can be used even when arguments
of recursive calls are not strictly decreasing,
but they might not get memoized. If this is not desired
use tabulateFix'
instead.
For example, here is a routine to measure the length of
Collatz sequence:
>>>
collatzF f n = if n <= 1 then 0 else 1 + f (if even n then n `quot` 2 else 3 * n + 1)
>>>
memoizeFix collatzF 27
111
Since: 0.3.0.0
Chimera
Lazy infinite streams with elements from a
,
backed by a Vector
v
(boxed, unboxed, storable, etc.).
Use tabulate
, tabulateFix
, etc. to create a stream
and index
to access its arbitrary elements
in constant time.
Since: 0.2.0.0
Instances
Construction
tabulateFix :: Vector v a => ((Word -> a) -> Word -> a) -> Chimera v a Source #
For a given f
create a stream of values of a recursive function fix
f
.
Once created it can be accessed via index
or toList
.
For example, imagine that we want to tabulate Catalan numbers:
>>>
catalan n = if n == 0 then 1 else sum [ catalan i * catalan (n - 1 - i) | i <- [0 .. n - 1] ]
Can we find catalanF
such that catalan
= fix
catalanF
?
Just replace all recursive calls to catalan
with f
:
>>>
catalanF f n = if n == 0 then 1 else sum [ f i * f (n - 1 - i) | i <- [0 .. n - 1] ]
Now we are ready to use tabulateFix
:
>>>
ch = tabulateFix catalanF :: VChimera Integer
>>>
index ch 9
4862>>>
take 10 (toList ch)
[1,1,2,5,14,42,132,429,1430,4862]
Note: Only recursive function calls with decreasing arguments are memoized.
If full memoization is desired, use tabulateFix'
instead.
Since: 0.2.0.0
tabulateFix' :: Vector v a => ((Word -> a) -> Word -> a) -> Chimera v a Source #
Fully memoizing version of tabulateFix
.
This function will tabulate every recursive call,
but might allocate a lot of memory in doing so.
For example, the following piece of code calculates the
highest number reached by the
Collatz sequence
of a given number, but also allocates tens of gigabytes of memory,
because the Collatz sequence will spike to very high numbers.
>>>
collatzF :: (Word -> Word) -> (Word -> Word)
>>>
collatzF _ 0 = 0
>>>
collatzF f n = if n <= 2 then 4 else n `max` f (if even n then n `quot` 2 else 3 * n + 1)
>>>
>>>
maximumBy (comparing $ index $ tabulateFix' collatzF) [0..1000000]
...
Using memoizeFix
instead fixes the problem:
>>>
maximumBy (comparing $ memoizeFix collatzF) [0..1000000]
56991483520
Since: 0.3.2.0
iterate :: Vector v a => (a -> a) -> a -> Chimera v a Source #
iterate
f
x
returns an infinite stream, generated by
repeated applications of f
to x
.
>>>
ch = iterate (+ 1) 0 :: UChimera Int
>>>
take 10 (toList ch)
[0,1,2,3,4,5,6,7,8,9]
Since: 0.3.0.0
cycle :: Vector v a => v a -> Chimera v a Source #
Return an infinite repetition of a given vector. Throw an error on an empty vector.
>>>
ch = cycle (Data.Vector.fromList [4, 2]) :: VChimera Int
>>>
take 10 (toList ch)
[4,2,4,2,4,2,4,2,4,2]
Since: 0.3.0.0
Create a stream of values from a given prefix, followed by default value afterwards.
Since: 0.3.3.0
Create a stream of values from a given prefix, followed by default value afterwards.
Since: 0.3.3.0
Manipulation
interleave :: Vector v a => Chimera v a -> Chimera v a -> Chimera v a Source #
Intertleave two streams, sourcing even elements from the first one and odd elements from the second one.
>>>
ch = interleave (tabulate id) (tabulate (+ 100)) :: UChimera Word
>>>
take 10 (toList ch)
[0,100,1,101,2,102,3,103,4,104]
Since: 0.3.3.0
Elimination
index :: Vector v a => Chimera v a -> Word -> a Source #
Index a stream in a constant time.
>>>
ch = tabulate (^ 2) :: UChimera Word
>>>
index ch 9
81
Since: 0.2.0.0
toList :: Vector v a => Chimera v a -> [a] Source #
Convert a stream to an infinite list.
>>>
ch = tabulate (^ 2) :: UChimera Word
>>>
take 10 (toList ch)
[0,1,4,9,16,25,36,49,64,81]
Since: 0.3.0.0
Monadic construction
Be careful: the stream is infinite, so monadic effects must be lazy in order to be executed in a finite time.
For instance, lazy state monad works fine:
>>>
import Control.Monad.State.Lazy
>>>
ch = evalState (tabulateM (\i -> do modify (+ i); get)) 0 :: UChimera Word
>>>
take 10 (toList ch)
[0,1,3,6,10,15,21,28,36,45]
But the same computation in the strict state monad Control.Monad.State.Strict diverges.
tabulateM :: (Monad m, Vector v a) => (Word -> m a) -> m (Chimera v a) Source #
Monadic version of tabulate
.
Since: 0.2.0.0
tabulateFixM :: (Monad m, Vector v a) => ((Word -> m a) -> Word -> m a) -> m (Chimera v a) Source #
Monadic version of tabulateFix
.
There are no particular guarantees about the order of recursive calls:
they may be executed more than once or executed in different order.
That said, monadic effects must be idempotent and commutative.
Since: 0.2.0.0
tabulateFixM' :: forall m v a. (Monad m, Vector v a) => ((Word -> m a) -> Word -> m a) -> m (Chimera v a) Source #
Monadic version of tabulateFix'
.
Since: 0.3.3.0
iterateM :: (Monad m, Vector v a) => (a -> m a) -> a -> m (Chimera v a) Source #
Monadic version of iterate
.
Since: 0.3.0.0
unfoldrM :: (Monad m, Vector v b) => (a -> m (b, a)) -> a -> m (Chimera v b) Source #
Monadic version of unfoldr
.
Since: 0.3.3.0
Subvectors
Internally Chimera
consists of a number of subvectors.
Following functions provide a low-level access to them.
This ability is especially important for streams of booleans.
Let us use Chimera
to memoize predicates f1
, f2
::
Word
->
Bool
.
Imagine them both already
caught in amber as ch1
, ch2
::
UChimera
Bool
,
and now we want to memoize f3 x = f1 x && f2 x
as ch3
.
One can do it in as follows:
ch3 = tabulate (\i -> index ch1 i && index ch2 i)
There are two unsatisfactory things here. Firstly,
even unboxed vectors store only one boolean per byte.
We would rather reach out for Bit
wrapper,
which provides an instance of unboxed vector
with one boolean per bit. Secondly, combining
existing predicates by indexing them and tabulating again
becomes relatively expensive, given how small and simple
our data is. Fortunately, there is an ultra-fast zipBits
to zip bit vectors. We can combine it altogether like this:
import Data.Bit import Data.Bits ch1 = tabulate (Bit . f1) ch2 = tabulate (Bit . f2) ch3 = zipWithSubvectors (zipBits (.&.)) ch1 ch2
mapSubvectors :: (Vector u a, Vector v b) => (u a -> v b) -> Chimera u a -> Chimera v b Source #
Map subvectors of a stream, using a given length-preserving function.
Since: 0.3.0.0
traverseSubvectors :: (Vector u a, Vector v b, Applicative m) => (u a -> m (v b)) -> Chimera u a -> m (Chimera v b) Source #
Traverse subvectors of a stream, using a given length-preserving function.
Be careful, because similar to tabulateM
, only lazy monadic effects can
be executed in a finite time: lazy state monad is fine, but strict one is
not.
Since: 0.3.3.0
zipSubvectors :: (Vector u a, Vector v b, Vector w c) => (u a -> v b -> w c) -> Chimera u a -> Chimera v b -> Chimera w c Source #
Deprecated: Use zipWithSubvectors instead
Since: 0.3.0.0
zipWithSubvectors :: (Vector u a, Vector v b, Vector w c) => (u a -> v b -> w c) -> Chimera u a -> Chimera v b -> Chimera w c Source #
Zip subvectors from two streams, using a given length-preserving function.
Since: 0.3.3.0
zipWithMSubvectors :: (Vector u a, Vector v b, Vector w c, Applicative m) => (u a -> v b -> m (w c)) -> Chimera u a -> Chimera v b -> m (Chimera w c) Source #
Zip subvectors from two streams, using a given monadic length-preserving function.
Caveats for tabulateM
and traverseSubvectors
apply.
Since: 0.3.3.0